1. Field of the Invention
The present invention relates to a method for automatically shifting the base line, and in particular to a method for compensating the shifting of the base line due to PM of tools.
2. Description of Related Art
With the development of semiconductor technology, more and more functional electronic devices related to semiconductor are manufactured. Consequently the semiconductor manufacturing processes is developed from 6 inches wafer to 12 inches wafer. The yield of the manufacturing processes has to be improved so as to increase the profit of product. Many statistic and analyzing methods have been developed and applied for monitoring the manufacturing parameters in order to achieve the high yield.
Now, the automatic manufacturing tools or equipment are used for manufacturing semiconductors and tools are arranged for predictive maintenance (PM) in order to maintain the function of tools. On the other hand, when the performance of the tools is under monitoring, it is necessary for repairing the tools. However, there is huge error in the parameter analysis due PM, for example, the base line of the tool shifts. Please refer to FIGS. 1 to 1B; a gas flow (i.e., processing data) and a length of structure (i.e., measurement data) are analyzed for figuring out the correlation. Because of the shifting of base line, the analyzed data separates into two zones and a correlation error occurs in this data distribution. FIG. 1 shows the processing data in time series (gas flow parameter in time series) and the measurement in time series (length in time series), and the broken lines define a PM section. FIG. 1A shows the base lines of processing section before predictive maintenance 10′, a predictive maintenance section 11′, and a processing section after predictive maintenance 12′ are shifted due to PM. FIG. 1B shows that there is correlation error in correlation analysis.
Traditional, the analyzer ignores the shifted section and simply selects the stable section to calculate the correlation. However, the data analysis is not precise because some information is missed. Furthermore, analyzer only the data excluded the data in PM section by experience. Thus, this method is used for selecting data point by human with low efficiency and the method has no coincidence for difference cases. In another words, the traditional method can not be used for analyzing a mount of data with high efficiency.
Therefore, in view of this, the inventor proposes the present invention to overcome the above problems based on his expert experience and deliberate research.